Triple
T15331845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haraldshaugen national monument |
E366553
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Haugesund |
E75231
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Haugesund | Statement: [Haraldshaugen national monument, locatedIn, Haugesund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haugesund Context triple: [Haraldshaugen national monument, locatedIn, Haugesund]
-
A.
Haugesund
chosen
Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
-
B.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
C.
Nordfjordeid
Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
-
D.
Sunndalsøra
Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
-
E.
Åkrehamn
Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0268608190947a58f559a67717 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f7d79348190aba1889a7eb3d7c8 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 3:17 a.m.